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Record W2913959620 · doi:10.7763/ijesd.2015.v6.574

Photocatalytic Degradation of 2, 4-D and Transition of Endocrine Disruptive Activity Using Transcriptome Based Bioassay in Zebrafish Embryos

2015· article· en· W2913959620 on OpenAlexaff
Aamer Saeed

Bibliographic record

VenueInternational Journal of Environmental Science and Development · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicPharmaceutical and Antibiotic Environmental Impacts
Canadian institutionsUniversity of Calgary
FundersHigher Education Commision, Pakistan
KeywordsBioassayZebrafishDegradation (telecommunications)TranscriptomeEndocrine systemEmbryoPhotocatalysisChemistryCell biologyBiologyBiochemistryEcologyHormoneGene expressionGeneComputer scienceCatalysis

Abstract

fetched live from OpenAlex

2, 4-Dichlorophenoxyacetic acid (2, 4-D) is one of the most widely used halogenated agricultural chemicals around the world and a well known endocrine disrupting chemical (EDC).TiO 2 based photocatalytic degradation of 2, 4-D was carried out and residual endocrine disruptive (ED) activity was determined by an in vivo model of zebrafish embryos exposed to various concentrations of 2, 4-D and its degraded products from 5 hpf (hours post fertilization) to 72 hpf.Quantitative Real Time PCR was carried out to determine the relative expression of Heat shock protein (HSP70) and Glutathione peroxidase (GPX) genes of zebrafish using ß-actin as housekeeping gene.HSP 70 expression increased at 150 µg/L 2, 4-D concentration while the expression was significantly lowered after its photocatalytic degradation.GPX expression was not significantly altered.The results reveal the validity of HSP gene affected by 2, 4-D exposure and some probability of toxic potential of byproducts formed during its degradation.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.042
GPT teacher head0.303
Teacher spread0.261 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2015
Admission routes1
Has abstractyes

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Same venueInternational Journal of Environmental Science and DevelopmentSame topicPharmaceutical and Antibiotic Environmental ImpactsFrench-language works237,207